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Chapter 7: Probability Distribution

Probability distributions are explanations of the probabilities that a random process will result in each of the possible specific outcomes. For instance, the probability distribution of a single roll of a standard die might look like:

1: 16.7%

2: 16.7%

3: 16.7%

4: 16.7%

5: 16.7%

6: 16.7%

Different types of probability measures require different probability distributions. Continuous random variables, for instance, have an infinite number of possible outcomes in any given interval, making it impossible to create a list of individual probabilities like the ones for the die above. In this chapter, you will learn how to create and interpret all kinds of probability distributions.

Chapter Summary

Students were introduced to the concepts of random variables and probability distributions. Instruction and exercises were provided to familiarize students with the interpretation and construction of various probability distribution tables and graphs. Binomial experiments were introduced, as were transformations of discrete random variables.

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Description

An examination of random variables, both discrete and continuous, and the related generation of probability distributions. Students become familiar with probability distribution graphs and tables, and the relationship between probability density functions and distribution visualizations. Later concepts introduce expected values and the variance of random variables, and finally examine transformations of random variables (operations on random variables).